US 11,702,103 B2
Affective-cognitive load based digital assistant
Adam Boulanger, Palo Alto, CA (US); Sven Kratz, Saratoga, CA (US); Joseph Verbeke, San Francisco, CA (US); Priya Seshadri, Stamford, CT (US); Evgeny Burmistrov, Saratoga, CA (US); Neeka Mansourian, El Dorado Hills, CA (US); and Stefan Marti, Oakland, CA (US)
Assigned to Harman International Industries, Incorporated, Stamford, CT (US)
Filed by HARMAN INTERNATIONAL INDUSTRIES, INCORPORATED, Stamford, CT (US)
Filed on Apr. 2, 2020, as Appl. No. 16/839,056.
Prior Publication US 2021/0309252 A1, Oct. 7, 2021
Int. Cl. B60W 60/00 (2020.01); B60W 40/08 (2012.01); G06F 3/01 (2006.01); G06V 20/59 (2022.01)
CPC B60W 60/0013 (2020.02) [B60W 40/08 (2013.01); G06F 3/013 (2013.01); G06F 3/015 (2013.01); G06V 20/597 (2022.01); B60W 2540/22 (2013.01); B60W 2540/221 (2020.02); B60W 2540/229 (2020.02); G06F 2203/011 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving, from at least one sensor, sensor data associated with an environment;
computing, based on the sensor data, a cognitive load value associated with a user within the environment;
computing, based on the sensor data, an arousal value and a valence value associated with an emotional state of the user;
multiplying the valence value by a combination of the cognitive load value and the arousal value to generate an affective-cognitive load;
comparing the affective-cognitive load with one or more thresholds to determine a user readiness state associated with the user; and
modifying a vehicle operation to assist the user in performing a driving action to a degree that corresponds to the user readiness state.